Abstract
Evidence has shown that the trend of increasing obesity rates has continued in the last decade. Mobile phone applications, benefiting from their ubiquity, have been increasingly used to address this issue. In order to increase the applications’ acceptance and success, a design and development process that focuses on users, such as user-centred design, is necessary. This paper reviews reported studies that concern the design and development of mobile phone applications to prevent obesity, and analyses them from a user-centred design perspective. Based on the review results, strengths and weaknesses of the existing studies were identified. Identified strengths included: evidence of the inclusion of multidisciplinary skills and perspectives; user involvement in studies; and the adoption of iterative design practices. Weaknesses included the lack of specificity in the selection of end-users and inconsistent evaluation protocols. The review was concluded by outlining issues and research areas that need to be addressed in the future, including: greater understanding of the effectiveness of sharing data between peers, privacy, and guidelines for designing for behavioural change through mobile phone applications.
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Finucane MM, Stevens GA, Cowan MJ, Danaei G, Lin JK, Paciorek CJ, Singh GM, Gutierrez HR, Lu Y, Bahalim AN, Farzadfar F, Riley LM, Ezzati M (2011) National, regional and global trends in body-mass index since 1980: systematic analysis of health examination surveys and epidemiological studies with 960 country-years and 9.1 million participants. Lancet 377(8765):557–567. doi:10.1016/S0140-6736(10)62037-5
Ogden CL, Caroll MD, Kit BK, Flegal KM (2012) Prevalence of obesity in the United States 2009–2010. National Centre for Health Statistic Data Brief, 82
Branca F, Haik N, Lobstein T (2007) The challenge of obesity in the WHO European Region and the strategies for response: summary. WHO, Copenhagen
Fry J, Finley W (2005) The prevalence and costs of obesity in the EU. Proc Nutr Soc 64(3):359–362. doi:10.1079/PNS2005443
Finkelstein EA, Fiebelkorn IC, Wang G (2003) National medical spending attributable to overweight and obesity: how much and who’s paying? Health Aff 3:219–226. doi:10.1377/hlthaff.w3.219
Nagai M, Kuriyama S, Kakizaki M, Ohmori-Matsuda K, Sone T, Hozawa A, Kawado M, Hashimoto S, Tsuii I (2012) Impact of obesity, overweight and underweight on life expectancy and lifetime medical expenditures: the Ohsaki Cohort Study. BMJ Open 2(3). doi:10.1136/bmjopen-2012-000940
Wang YC, McPherson K, Marsh T, Gortmaker SL, Brown M (2011) Health and economic burden of the projected obesity trends in the USA and UK. Lancet 378(9739):815–825. doi:10.1016/S0140-6736(11)60814-3
Ollberding NJ, Wolf RL, Contento I (2010) Food label use and its relation to dietary intake among US adults. J Am Diet Assoc 100(8):1233–1237. doi:10.1016/j.jada.2010.05.007
Mytton OT (2012) Taxing unhealthy food and drinks to improve health. Br Med J 344:e2931. doi:10.1136/bmj.e2931
Klasnja P, Pratt W (2012) Healthcare in the pocket: mapping the space of mobile-phone health interventions. J Biomed Inform 45:184–198. doi:10.1016/j.jbi.2011.08.017
Lau PWC, Lau EY, Wong DP, Ransdell L (2011) A systematic review of information and communication technology-based interventions for promoting physical activity behavior change in children and adolescents. J Med Intern Res 13(3). doi:10.2196/jmir.1533
Kennedy CM., Powell J, Payne TH, Ainsworth J, Boyd A, Buchan I (2012) Active assistance technology for health-related behavior change: an interdisciplinary review. J Med Intern Res 14(3). doi:10.2196/jmir.1893
Damodaran L (1996) User involvement in the system design process—a practical guide for users. Behav Inf Technol 15(6):364–377
Norman DA, Draper SW (1986) User-centred system design: new perspective on human–computer interaction. Lawrence Earlbaum Associate, Hillsdale
Preece J, Rogers Y, Sharp H, Benyon D, Holland S, Carey T (1994) Human computer interaction. Pearson Education Limited, England
Maguire M, Bevan N (2002) User requirements analysis: a review of supporting methods. In: Proceedings of IFIP 17th World Computer Congress
Maguire M (2001) Methods to support human-centred design. Int J Hum Comput Stud 55:587–634
Vredenburg K, Isensee S, Righi C (2002) User-centred design: an integrated approach. Prentice-Hall, New Jersey
Hartson R, Pyla P (2012) The UX book: process and guidelines for ensuring a quality user experience. Elsevier, Waltham
Iglesias J, Cano J, Bernardos AM, Casar JR (2011a) A ubiquitous cavity-monitor to prevent sedentaries. In Proceedings of IEEE international conference on pervasive computing and communications
Iglesias J, Bernardos AM, Tarrio P, Casar JR, Martin H (2011b) Design and validation of a light inference system to support embedded context reasoning. Pers Ubiquit Comput
Fialho ATS, van den Heuvel H, Shahab Q, Liu Q, Li L, Saini P, Lacroix J, Markopoulos P (2009a) ActiveShare: sharing challenges to increase physical activities. In: Proceedings of the 27th international conference on human factors in computing systems. doi:10.1145/1520340.1520633
Fialho A, van den Heuvel H, Shahab Q, Liu Q, Li L, Saini P, Lacroix J, Markopoulos P (2009b) Virtual challenges: a social interaction approach to increasing physical activity. In: Wouters IHC, Tieben R, Kimman FFP, Offermans SAM, Nagtzaam HAH (eds) Flirting with the future: proceedings of the 5th student interaction design conference
Arteaga SM, Kudeki M, Woodworth A (2009) Combating obesity trends in teenagers through persuasive mobile technology. SIGACCESS Access Comput 94:17–25. doi:10.1145/1595061.1595064
Arteaga SM, Kudeki M, Woodworth A, Kurniawan S (2010) Mobile system to motivate teenagers’ physical activity. In: Proceedings of the 9th international conference on interaction design and children. doi:10.1145/1810543.1810545
Arteaga SM (2010) Persuasive mobile exercise companion for teenagers with weight management issues. SIGACCESS Access Comput 96:4–10. doi:10.1145/1731849.1731850
Denning T, Andrew A, Chaudhri R, Hartung C, Lester J, Borriello G, Duncan G (2009) BALANCE: towards a usable pervasive wellness application with accurate activity inference. In: Proceedings of the 10th workshop on mobile computing systems and applications. doi:10.1145/1514411.1514416
Andrew A, Denning T, Borriello G (2009) BALANCE: An engaging interface for long term wellness. In: Proceedings of the computer and human interactions 2009 conference
Hughes DC, Andrew A, Denning T, Hurvitz P, Lester J, Beresford S, Borriello G, Bruemmer B, Moudon AV, Duncan GE (2010) BALANCE (Bioengineering Approaches for Lifestyle Activity and Nutrition Continuous Engagement): developing new technology for monitoring energy balance in real time. J Diabetes Sci Technol 4(2):429–434
Toscos T, Faber A, An S, Gandhi MF (2006) Chick clique: persuasive technology to motivate teenage girls to exercise. In: Proceedings of the computer and human interaction 2006 conference. doi:10.1145/1125451.1125805
Toscos T, Faber A, Connelly K, Upoma AM (2008) Encouraging physical activity in teens: can technology help reduce barriers to physical activity in adolescent girls? In: Proceedings of pervasive computing technologies for healthcare. doi:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.206.1225
Clark D, Edmonds C, Moore A, Harlow J, Allen K (2012) Android application development to promote physical activity in adolescents. In: Proceedings of 2012 international conference on the collaboration technologies and systems (CTS). doi:10.1109/CTS.2012.6261106
Allen K, Harlow J, Cook E, McCrickard DS, Winchester WW III, Zoellner J, Estabrooks P (2012) Understanding perceptions and experiences of cellular phone usage in low socioeconomic youth. In: Proceedings of the 33rd annual meeting and scientific sessions of the society for behavioral medicine
Schiel R, Kaps A, Bieber G (2012) Electronic health technology for the assessment of physical activity and eating habits in children and adolescents with overweight and obesity IDA. Appetite 58(2):432–437. doi:10.1111/j.1744-9987.2010.00903
Bieber G, Voskamp J, Urban B (2009) Activity recognition for everyday life on mobile phones. In: Proceedings of the 5th international on conference universal access in human–computer interaction. doi:10.1007/978-3-642-02710-9_32
Shang J, Sundara-Rajan K, Lindsey L, Mamishev A, Johnson E, Teredesei A, Kristal A (2011a) A pervasive dietary data recording system. In: Proceedings of IEEE international conference on pervasive computing and communications. doi:10.1109/PERCOMW.2011.5766890
Shang J, Sundara-Rajan K, Lindsey L, Mamishev A, Johnson E, Teredesei A, Kristal A (2011b) A mobile structured light system for food volume evaluation. In: Proceedings of IEEE international conference on computer vision workshops. doi:10.1109/ICCVW.2011.6130229
Shang J, Pepin E, Johnson E, Hazel D, Teredesai A, Kristal A, Mamishev A (2012). Dietary intake assessment using integrated sensors and software. In: Proceedings of SPIE 8304 multimedia on mobile devices. doi:10.1117/12.907769
Kong F, Tan J (2012) DietCam: automatic dietary assessment with mobile camera phones. Pervasive Mob Comput 8:147–163. doi:10.1016/j.pmcj.2011.07.003
Clawson J, Patel N, Starner T (2010) Dancing in the Streets: The design and evaluation of a wearable health game. In: Proceedings of the 2010 international symposium on wearable computers. doi:10.1109/ISWC.2010.5665864
Ho TC, Chen X (2009) ExerTrek: a portable handheld exercise monitoring, tracking and recommendation system. In: Proceedings of the 11th international conference on e-health networking, applications and services. doi:10.1109/HEALTH.2009.5406194
Laikari A (2009) Exergaming—gaming for health: a bridge between real world and virtual communities. In: Proceedings of the 13th IEEE international symposium on consumer electronics. doi:10.1109/ISCE.2009.5157004
Vaatanen A, Leikas J (2009) Human-centred design and exercise games: users’ experiences of a fitness adventure prototype. In: Kankaanranta M, Neittaanmaki P (eds) Design and use of serious games. Springer, Dordrecht
Chuah M, Sample S (2011) Fitness Tour: a mobile application for combating obesity. In: Proceedings of the first ACM MobiHoc workshop on pervasive wireless healthcare. doi:10.1145/2007036.2007048
Kitamura K, Yamasaki T, Aizawa K (2009) Food image analysis by local image feature. IEICE Tech Report 108(425):167–172
Aizawa K, de Silva GC, Ogawa M, Sato Y (2010) Food log by snapping and processing images. In: Proceedings of international conference on virtual systems and multimedia (VSMM). doi:10.1109/VSMM.2010.5665963
Chang T (2012) Food fight: A social diet network mobile application. Master Thesis, University of California
Wylie CG, Coulton P (2008) Mobile exergaming. In: Proceedings of 2008 international conference on advances in computer entertainment technology. doi:10.1145/1501750.1501830
Wylie CG, Coulton P (2009) Mobile persuasive exergaming. In: Proceedings of international IEEE consumer electronics society’s games innovations conference. doi:10.1109/ICEGIC.2009.5293582
Gao C, Fanyu K, Tan J (2009) Health aware: tackling obesity with health aware smart phone systems. In: Proceedings of the 2009 IEEE international conference on robotics and biomimetics. doi:10.1007/s11036-007-0014-4
Consolvo S, Everitt K, Smith I, Landay JA (2006) Design requirements for technologies that encourage physical activity. In: Proceedings of CHI 2006. doi:10.1145/1124772.1124840
Consolvo S, Harrison B, Smith I, Chen M, Everitt K, Froelich J, Landay JA (2007) Conducting in situ evaluations for and with ubiquitous computing technologies. Int J Hum Comput Interact 22(1):107–122. doi:10.1080/10447310709336957
Järvinen P, Järvinen T.H, Lähteenmäki L, Södergård C (2008) HyperFit: hybrid media in personal nutrition and exercise management. In: Proceedings of second international conference on pervasive computing technologies for healthcare. doi:10.4108/ICST.PERVASIVEHEALTH2008.2555
Macvean A, Robertson J (2012) iFitQuest: a school based study of a mobile location-aware exergame for adolescents. In: Proceedings of the 14th international conference on human–computer interaction with mobile devices and services. doi:10.1145/2371574.2371630
Macvean A (2012) Developing adaptive exergames for adolescent children. In: Proceedings of the 11th international conference on interaction design and children. doi:10.1145/2307096.2307162
Li I, Key AK, Forlizzi J (2012) Using context to reveal factors that affect physical activity. J ACM Trans Comput Hum Interact 19(1). doi:10.1145/2147783.2147790
Ahtinen A, Huuskonen P, Hakkila J (2010) Let’s all get up and walk to the north pole: design and evaluation of a mobile wellness application. In: Proceedings of the 6th nordic conference on human–computer interaction. doi:10.1145/1868914.1868920
Emken BA, Li M, Thatte G, Annavaram M, Mitra U, Narayanan S, Sprujit-Metz D (2012) Recognition of physical activities in overweight Hispanic youth using KNOWME networks. J Phys Act Health 9(3):432–441
Chittaro L, Sioni R (2012) Turning the classic snake mobile game into a location-based exergame that encourages walking. In: Proceedings of the 7th international conference on persuasive technology: design for health and safety. doi:10.1007/978-3-642-31037-9_4
Gorgu L, O’Hare GMP, O’Grady MJ (2009) Towards mobile collaborative exergaming. In: Proceedings of the second international conference on advances in human-oriented and personalized mechanisms, technologies, and services. doi:10.1109/CENTRIC.2009.16.61
Bentley F, Tollmar K, Viedma C (2012) Personal health mahsups: mining significant observations from wellbeing data and context. In Proceedings of CHI 2012
Tollmar K, Bentley F, Viedma C (2012) Mobile health mashups: making sense of multiple streams of wellbeing and contextual data for presentation on a mobile device. In: Proceedings of 6th international conference on pervasive computing technologies for healthcare and workshops. doi:10.4108/icst.pervasivehealth.2012.248698
Khan DU, Ananthanarayan S, Le A, Schaefbauer CL, Siek KA (2012) Designing mobile snack application for low socioeconomic status families. In: Proceedings of the 6th international conference on pervasive computing technologies for health care. doi:10.4108/icst.pervasivehealth.2012.248692
Buttusi F, Chittaro L (2010) Smarter phones for healthier lifestyle: an adaptive fitness game. Pervasive Comput 9(4):51–57. doi:10.1109/MPRV.2010.52
Buttusi F, Chittaro L, Nadalutti, D (2006) Bringing mobile guides and fitness activities together: a solution based on an embodied virtual trainer. In: Proceedings of the 8th conference on human–computer interaction with mobile devices and services. doi:10.1145/1152215.1152222
Buttusi F, Chittaro L (2008) MOPET: a context-aware and user-adaptive wearable system for fitness training. Artif Intell Med 42(2):153–163. doi:10.1016/j.artmed.2007.11.004
Lin Y, Jessurun J, de Vries B, Timmermans H (2011a) Motivate: context aware mobile application for activity recommendation. In: Proceedings of the 2nd international conference on ambient intelligence. doi:10.1007/978-3-642-25167-2_27
Lin Y, Jessurun J, de Vries B, Timmermans H (2011b) Motivate: towards context aware recommendation mobile system for healthy living. In: Proceedings of the 5th international conference on pervasive computing technologies for healthcare and workshops. doi:10.4108/icst.pervasivehealth.2011.246030
Bielik P, Tomlein M, Kratky S, Barla M, Bielikova M (2012) Move2Play: an innovative approach to encouraging people to be more physically active. In: Proceedings of the 2nd ACM SIGHIT international health informatics symposium. doi:10.1145/2110363.2110374
Fukuoka Y, Lindgren T, Jong S (2012) Qualitative exploration of the acceptability of a mobile phone and pedometer-based physical activity program in a diverse sample of sedentary women. Public Health Nurs 29(3):232–240. doi:10.1111/j.1525-1446.2011.00997
Fukuoka Y, Komatsu J, Suarez L, Vittinghoff E, Haskell W, Noorishad T, Pham K (2011) The mPED randomised controlled clinical trial: applying mobile persuasive technologies to increase physical activity in sedentary women protocol. BMC Public Health 11:933. doi:10.1186/1471-2458-11-933
Fujiki Y, Starren J, Kazakos K, Pavlidis I, Puri C, Levine J (2007) NEAT-o-games: ubiquitous activity-based gaming. In: Proceedings of CHI 2007. doi:10.1145/1240866.1241009
Fujiki Y, Kazakos K, Puri C, Buddharaju P, Pavlidia I, Levine J (2008) NEAT-o-games: blending physical activity and fun in the daily routine. ACM Comput Entertain. 6(1). doi:10.1145/1371216.1371224
Kazakos K, Fujiki Y, Pavlidis I, Bourlai T, Levine J (2008) NEAT-o-games: novel mobile gaming versus modern sedentary lifestyle. In: Proceedings of MobileHCI 2008. doi:10.1145/1409240.1409333
Grimes A, Kantroo V, Grinter RE (2010) Let’s play!: mobile health games for adults. In: Proceedings of the 12th ACM international conference on ubiquitous computing. doi:10.1145/1864349.1864370
Grimes A, Grinter R (2007) Designing persuasion: health technology for low-income african american communities. In: Proceedings of the 2nd international conference on persuasive technology
van Gils M, Parkka J, Lappalainen R, Ahonen A, Maukonen A, Tuomisto T (2001) Feasibility and user acceptance of a personal weight management system based on ubiquitous computing. In: Proceedings of the 23rd annual IEEE international conference on engineering in medicine and biology society. doi:10.1109/IEMBS.2001.1019626
Parkka J, van Gils M, Tuomisto T (2000) A wireless wellness monitor for personal weight management. In Proceedings of 2000 IEEE engineering in medicine and biology society
Lee G, Raab F, Tsai C, Patrick K, Griswold WG (2007) PmEB: a mobile phone application for monitoring caloric balance. In: Proceedings of CHI 2006. doi:10.1007/s11036-007-0014-4
Tsai CC, Lee G, Raab F, Norman GJ, Sohn T, Griswold WG, Patrick K (2007) Usability and feasibility of PmEB: a mobile phone application for monitoring real time caloric balance. Mob Netw Appl 12:173–184. doi:10.1007/s11036-007-0014-4
Berkovsky S, Freyne J, Coombe M (2012) Physical activity motivating games: be active and get your own reward. J ACM Trans Comput Hum Interact 19(4). doi:10.1145/2395131.2395139
Rodrigues JJ, Lopes IM, Silva BM, Torre ID (2012) A new mobile ubiquitous computing application to control obesity: SapoFit. Inf Health Soc Care. doi:10.3109/17538157.2012.674586
Silva BM, Lopes IM, Rodrigues JJ, Ray P (2011) SapoFitness: a mobile health application for dietary evaluation. In: Proceedings of 18th international conference on e-health networking, applications and services
Maitland J, Sherwood S, Barkhuus L, Anderson I, Hall M, Brown B, Chalmers M, Muller M (2006) Increasing the awareness of daily levels with pervasive computing. In: Proceedings of pervasive health conference and workshop. doi:10.1109/PCTHEALTH.2006.361667
Anderson I, Maitland J, Sherwood S, Barkhuus L, Chalmers M, Hall M, Brown B, Muller H (2007) Shakra: tracking and sharing daily activity levels with unaugmented mobile phones. Mob Netw Appl 12:185–199
Kuehn E, Sieck, J (2010) Location and situation based services for pervasive adventure games. In: Proceedings of 12th international conference on computer modelling and simulation. doi:10.1109/UKSIM
Kuehn E, Sieck J (2009) Design and implementation of location and situation based services for a pervasive mobile adventure game. In: Proceedings of IEEE international workshop on intelligent data acquisition and advanced computing systems: technology and applications. doi:10.1109/2010.95UKSIM
Reed AA, Samuel B, Sullivan A, Grant R, Grow A, Lazaro J, Mahal J, Kurniawan S, Walker M, Wardrip-Fruin N (2011a) SpyFeet: an exercise RPG. In: Proceedings of the 6th international conference on the foundation of digital games
Reed A A, Samuel B, Sullivan A, Grant R, Grow A, Lazaro J, Mahal J, Kurniawan S, Walker M, Wardrip-Fruin N (2011b) A step towards the future of role-playing games: The SpyFeet mobile {RPG} project. In: Proceedings of the 7th annual international artificial intelligence and interactive digital entertainment conference
Khalil A, Glal S (2009) StepUp: a step counter mobile application to promote healthy lifestyle. In: Proceedings of the 2009 international conference on the current trends in information technology. doi:10.1109/CTIT.2009.5423113
Zhu F, Bosch M, Boushey C J, Delp E J (2010) An image analysis system for dietary assessment and evaluation. In: Proceedings of 2010 IEEE 17th international conference on image processing. doi:10.1109/ICIP.2010.5650848
Khanna N, Boushey CJ, Kerr D, Okos M, Ebert DS, Delp EJ (2010) An overview of the technology assisted dietary assessment project at Purdue University. In: Proceedings of 2010 IEEE international symposium on multimedia. doi:10.1109/ISM.2010.50
Six BL, Tusarebeca ES, Fengqing Z, Mariappan A, Bosch M, Delp EJ, Ebert DS, Kerr DA, Houshey CJ (2010) Evidence-based development of a mobile telephone food record. J Am Diet Assoc 110:74–79. doi:10.1016/j.jada.2009.10.010
Pollak JP, Gay G, Bryne S, Wagner W, Retelny D, Humphreys L (2010) It’s time to eat! Using mobile games to promote healthy eating. Pervasive Comput 9(3):21–27. doi:10.1109/MPRV.2010.41
Bryne S, Gay G, Pollack JP, Gonzales A, Retelny D, Lee T, Wansink B (2012) Caring for mobile phone-based virtual pets can influence youth eating behaviours. J Child Media 6(1):83–99. doi:10.1080/17482798.2011.633410
Oliveira R, Oliver N (2008) TripleBeat: enhancing exercise performance with persuasion. In: Proceedings of MobileHCI 2008. doi:10.1145/1409240.1409268
Consolvo S, McDonald DW, Toscos T, Chen MY, Froehlich J, Harrison B, Klasnja P, LaMarc A, LeGrand L, Libby R, Smith I, Landay JA (2008a) Activity sensing in the wild: a field trial of UbiFit garden. In: Proceedings of CHI 2008. doi:10.1145/1357054.1357335
Consolvo S, Klasnja P, McDonald DW, Avrahami D, Froehlich J, LeGrand L, Mosher K, Landay JA (2008b) Flowers or a robot army? Encouraging awareness and activity with personal, mobile displays. In: Proceedings of the 10th international conference on ubiquitous computing. doi:10.1145/1409635.1409644
Consolvo S, Klasnja P, McDonald DW, Landay JA (2009a) Goal-setting considerations for persuasive technologies that encourage physical activity. In: Proceedings of the international conference on persuasive technology. doi:10.1145/1541948.1541960
Consolvo S, McDonald DW, Landay JA (2009b) Theory-driven design strategies for technologies that support behaviour change in everyday life. In: Proceedings of the 27th international conference on human factors in computing systems. doi:10.1145/1518701.1518766
Klasnja P, Consolvo S, McDonald, DW, Landay JA, Pratt W (2009a) Using mobile and personal sensing technologies to support health behaviour change in everyday life: lessons learned. In: Proceedings of the annual conference of the American medical informatics association. doi:http://www.ncbi.nlm.nih.gov/pubmed/20351876
Hamilton I, Imperatore G, Dunlop M, Rowe D, Hewitt A(2012) Walk2Build : a GPS game for mobile exergaming with city visualization. In: Proceedings of MobileHCI 2012
Freyne J, Bhandari D, Shlomo B, Borlyse L, Campbell C, Chau S (2010) Mobile mentor: weight management platform. In: Proceedings of the 15th international conference on intelligent user interface. doi:10.1145/1719970.1720046
Freyne J, Brindal E, Hendrie G, Berkovsky S, Coombe M (2012) Mobile applications to support dietary change: highlighting the importance of evaluation context. In: Proceedings of human factors in computing systems CHI EA. doi:10.1145/2212776.2223709
Mattila E, Parkka J, Hermersdorf M, Kaasinen J, Vainio J, Samposalo K, Merilahti J, Kolari J, Kulju M, Lappalainen R, Korhonen I (2008) Mobile diary for wellness management-results on usage and usability in two user studies. IEEE Trans Inf Technol Biomed 12(4):501–511. doi:10.1109/TITB.2007.908237
Mattila E (2010) Design and evaluation of a mobile phone diary for personal health management. Doctoral Thesis, VTT Technical Research Centre of Finland
Mattila E, Lappalainen R, Parkka J, Salminen J, Korhonen I (2010) Use of a a mobile phone diary for observing weight management and related behaviours. J Telemed Telecare 16(5):260–264. doi:10.1258/jtt.2009.091103
Mattila E, Korhonen I, Salminen J, Ahtinen A, Koskinen E, Sarela A, Parlka J, Lappalainen R (2010) Empowering citizens for well-being and chronic disease management with wellness diary. IEEE Trans Inf Technol Biomed 14(2):456–463. doi:10.1109/TITB.2009.2037751
Chuah M, Jakes G, Qin Z (2012) WifiTreasureHunt: a mobile social application for staying active physically. In: Proceedings of the 2012 ACM conference on ubiquitous computing. doi:10.1145/2370216.2370339
Intille SS, Albinali F, Mota S, Kuris B, Botana P, Haskell WL (2011) Design of a wearable physical activity monitoring system using mobile phones and accelerometers. In: Proceedings of the 33rd annual international conference of the IEEE engineering in medicine and biology society. doi:10.1109/IEMBS.2011.6090611
Doran K, Pickford S, Austin C, Walker T, Barnes T (2010) World of workout: towards pervasive intrinsically motivated, mobile exergaming. In: Proceedings of meaningful play
Gerrig RJ (1993) Experiencing narrative worlds: on the psychological activities of reading. Yale University Press, New Haven
Green MC, Brock TC (2000) The role of transportation in the persuasiveness of public narratives. J Pers Soc Psychol 79(5):701–721. doi:10.1037/0022-3514.79.5.701
Weinstein ND, Sandman PM (1992) A model of the precaution adoption process: evidence from home radon testing. Health Psychol 1193:170–180. doi:10.1037/0278-6133.11.3.170
Bandura A (1986) Social foundations of thought and action: A social cognitive theory. Prentice-Hall, Englewood Cliffs
Hassenzahl M, Burmester M, Koller F (2003) AttrakDiff: questionnaire to measure perceived hedonic and pragmatic quality. In: Ziegler J, Szwillus G (ed) Mensch and Computer 2003: Interaktion in Bewegung, pp 187–196
van den Berg MH, Schoones JW, Vlieland TPMV (2007) Internet-based physical activity interventions: a systematic review of the literature. J Med Internet Res 9(3). doi:10.2196/jmir.9.3.e26
Whiteley JA, Bailey BW, McInnis KJ (2008) State of the art reviews: Using the internet to promote physical activity and healthy eating in youth. Am J Lifestyle Med 2. doi:10.1177/1559827607311787
Arem H, Irwin M (2010) A review of web-based weight loss interventions in adults. Obes Manag 787:236–243
Mitchell WL, Economou D, Randall D (2000) God is an alien: understanding informant responses through user participation and observation. In: Proceedings of PDC2000 6th biennial participatory design conference
Scaife M, Rogers Y, Aldrich F, Davies M (1997) Designing for or designing with? Informant design for interactive learning environments. In: Proceedings of CHI ‘97: human factors in computing systems
Nielsen J (1994) Heuristic evaluation. In: Nielsen J, Mack RL (eds) Usability inspection methods. Wiley, New York
Lewis C, Wharton C (1997) Cognitive walkthroughs. In: Helander M (ed) A guide to human factors and ergonomics. CRC Press, USA
Noar SM, Harrington NG, Van Stee SKV, Aldrich RS (2011) Tailored health communication to change lifestyle behaviours. Am J Lifestyle Med 5:112–122. doi:10.1177/1559827610387255
Krebs P, Prochaska JO, Rossi JS (2010) A meta-analysis of computer-tailored interventions for health behaviour change. Prev Med 51:214–221. doi:10.1016/j.ypmed.2010.06.004
Prochaska J, Velicer W (1997) The transtheoretical model of health behavior change. Am J Health Promot 12(1):38–48
Duncan S (2005) Sources and types of social support in youth physical activity. Health Psychol 24:3–10. doi:10.1037/0278-6133.24.1.3
Voorhees CC, Murray D, Welk G, Birnbaum A, Ribisl KM, Johnson CC, Pfeiffer KA, Saksvig B, Jobe JB (2005) Role of peer social network factors and physical activity in adolescent girls. Am J Health Behav 29:183–190. doi:10.5993/AJHB.29.2.9
Consolvo, S., Everitt, K., Smith, I., Landay, J. A., 2006. Design requirements for technologies that encourage physical activity. In: Proceedings of CHI 2006
Klasnja P, Consolvo S, Choudhury T, Beckwith R, Hightower J (2009b) Exploring privacy concerns about personal sensing. In: Proceedings of the 7th international conference on pervasive putting. doi:10.1007/978-3-642-01516-8_13
Mutsuddi AU, Connelly K (2012) Text messages for encouraging physical activity: are they effective after the novelty effect wears off?. In: Proceedings of the 6th international conference on pervasive computing technologies for healthcare (Pervasive Health) and workshops. doi:10.4108/icst.pervasivehealth.2012.248715
Fogg BJ (2003) Persuasive technology: using computers to change what we think and do (interactive technologies). Morgan Kaufmann, Masssachusetts
Lenert L, Norman GJ, Mailhot M, Patrick K (2005) A framework for modeling health behavior protocols and their linkage to behavioural theory. J Biomed Inform 38:270–280. doi:10.1016/j.jbi.2004.12.001
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Appendices
Appendix 1: A brief overview of mobile phones applications that were included in the review
Underlying design concept | Targeted users | Role | Aim | Description of application | ||
---|---|---|---|---|---|---|
1. | Self-awareness | Not explicitly specified | Tracking | Increasing physical activity | A context-aware mobile application that is based on recognition of movement and location capable to enable estimation and evaluation of the user’s activity all day long | |
2. | Self-awareness and social goal setting | Individual with sedentary life style | Enforcing social influence | Increasing physical activities | Users share goals by proposing physical activity challenges to others. Accepted physical activity challenge becomes new goal, and recorded physical activities are shared among users | |
3. | Theory of planned behaviour, theory of meaning behaviour and personality theory | Teenagers | Entertainment | Increasing physical activity | Users’ personalities are identified and used to determine set of games relevant to their personalities. Motivational agent provides encouragement and positive reinforcement. User recorded manually the duration spent to play game | |
4. | Not indicated | Not explicitly specified | Tracking | Monitoring lifestyle | Users are provided with real-time feedback of their caloric intake/expenditure balance throughout the day by capturing their caloric intake through manual entries of food diaries and caloric expenditure through automatic detection of physical activity | |
5. | Goal setting, self-monitoring, positive reinforcement and social support | Teenage girls | Enforcing social influence | Increasing physical activity | Providing a group support system to promote walking towards a self-established daily step goals. Users entered step counts and shared them within the group with text message notification of step updates. Users can send motivating text messages to all or individual members of the group | |
6. | Not indicated | Adolescents | Entertainment | Increasing physical activity | A suite of three different game applications to promote physical activities utilising accelerometer | |
7. | Not indicated | Children and adolescent obesity and overweight | Tracking | Automatic recording of food and physical activity | Users’ physical activities are recorded automatically through motion sensors. Users recorded their food intake by taking photos of each meat at the beginning which are later analysed manually by nutritionist | |
8. | Not indicated | Not explicitly specified | Tracking | Automatic recording of food intake | Users are able to automatically calculate and log the caloric content of over nine thousand types of food, through the use a laser grid and a camera equipped mobile phone. Users are allowed to view an up-to-date summary of their daily eating habits | |
9. | DietCam [39] | Not indicated | Not explicitly specified | Tracking | Automatic recording of food intake | Users take three images or a short video of the meal (prior and after the meal). Images/videos are then used to recognise, classify and estimate the volume and calorie content of the meal |
10. | DiTS [40] | Not indicated | Children with obesity | Entertainment | Increasing physical activity | A mobile phone version of the popular arcade game on dancing. Users worn 3-axis accelerometers that are worn around the players’ ankles which record their legs movement with mobile phones to control the game and to display graphics |
11. | ExerTrek [41] | Not indicated | Not explicitly specified | Tracking | Optimising physical activity’s benefit | An exercise monitor on the mobile phone that will help an individual achieve a certain goal that users want from doing exercise. Once the goals and personal information are set for the individuals, it advises users to achieve the maximal benefits of their exercise without going beyond their own limits |
12. | Not indicated | Not explicitly specified | Entertainment | Increasing outdoor physical activity | An application platform to support physical outdoor exercise. It utilises location information and a mobile phone acts as a terminal device for the game | |
13. | Fitness tour [44] | Not indicated | School children and college students | Entertainment | To increase physical activity | Users are assigned an exercise tour, containing several locations, and shared their achievement through social media. Users’ verification are required at each location. Users’ heart beat were recorded at the start and end of the tour through a mobile phone’s camera |
14. | Not indicated | Not explicitly specified | Tracking | Automatic recording of food intake | Users take photos of their food intake which are then analysed to estimate the nutritional composition of the meals. The food images and their calorie content are stored in a database and accessible to users who can also revise the calorie information | |
15. | Food fight [47] | Not indicated | Adult | Entertainment | Education in nutrition and healthy eating | Introducing competition between users through comparisons of their diets and the rating of their diet |
16. | Persuasive design | Not explicitly specified | Entertainment | Increasing physical activity | Users are required to make certain physical movement while wearing accelerometer as the primary game mechanic | |
17. | HealthAware [50] | Not indicated | Not explicitly specified | Tracking | Monitoring lifestyle | Users monitor daily physical activity through embedded accelerometer and analyse food item by capturing food image with camera. Users are presented with activity counts at real time |
18. | Persuasive design | Individuals with obesity | Enforcing social influence | Increasing physical activity | Users are encouraged to perform physical activity by sharing step count with friends | |
19. | HyperFit [53] | Not indicated | Individuals with overweight issue | Tracking | Mimic personal nutrition counselling | Users are provided with self-evaluation tools for testing and goal definition, food and exercise diaries, analysis tools, and feedback and encouragement given by a virtual trainer |
20. | Not indicated | Adolescents | Entertainment | To increase physical activity | Users’ real world physical movement is used to control their virtual character, interact with Non-Player Character, visit landmarks and collect game items | |
21. | Impact [56] | Self-awareness | People with sedentary life style | Tracking | Monitoring physical activities | Users can capture number of steps, manually input the context of activities and review them on a web |
22. | Into [57] | Not indicated | Not explicitly specified | Tracking | To increase physical activity | The number of steps of a user, automatically recorded by in-built pedometer in a phone, is used to “proceed” (travel virtually) on a map. A use can play as an individual or a member of team |
23. | KnowME [58] | Not indicated | Overweight youth | Tracking | Monitoring physical activities | Users’ biometric signals of users are monitored and visualising users’ level of physical activity and sedentary behaviour |
24. | LocoSnake [59] | Not indicated | Not explicitly specified | Entertainment | To increase physical activity | A player embodies the snake and walks in the physical world to control it and get points |
25. | Luften [60] | Not indicated | Children with obesity or overweight issues | Entertainment | Increasing physical activity | Players are encouraged to move between the different zones through defined routes as their objectives of the game |
26. | Not indicated | Not explicitly specified | Tracking | Monitoring lifestyle | Users are provided with a mobile service that collects data from a variety of health and well-being sensors and presented significant correlations across sensors in a mobile widget as well as on a mobile web application | |
27. | Mobile snack [63] | Social cognitive theory, health belief model, elaboration likelihood model, transportation theory and the precaution adoption process model | Low socioeconomic status families | Tracking | Monitoring food intake | Users are provided with features to input and monitor snacking behaviour and receive feedback on snack healthiness |
28. | Monster and Gold [64] | Not indicated | People with sedentary life style | Entertainment | Trains and motivate users to jog outdoors | Users are provided with a context-aware and user-adaptive game which takes into account their heart rate, age, fitness level, and exercise phase |
29. | Not indicated | Not explicitly specified | Advisory | Trains and motivate users to jog and perform exercise outdoors | User’s positions during physical activity in an outdoor fitness trail are monitored to provide navigation assistance by using a fitness trail map and giving speech directions. An embodied virtual trainer shows how to correctly perform the exercises along the trail with 3D animations | |
30. | Persuasive design | Not explicitly specified | Advisory | Physical activity recommendation | Provides users with and contextualized advice on possible physical activities to do | |
31. | Move2PlayKids [69] | Goal setting, Self-awareness | Children aged 10–18 | Tracking | To increase physical activity | Users’ number of steps is obtained and their activities are inferred through GPS |
32. | Not indicated | Sedentary women | Tracking | Increasing physical activity | The mobile phone serves as a means of delivering the physical activity intervention, setting individualized weekly physical activity goals, and providing self-monitoring (activity diary), immediate feedback and social support. The mobile phone also functions as a tool for communication and real-time data capture | |
33. | Not indicated | Not explicitly specified | Entertainment | Increasing physical activity | Users physical activity are monitored and their level of activities control the animation of their avatars in a virtual race game with other players over the cellular network. Winners are declared every day and players with an excess of activity points are given rewards | |
34. | Transtheoretical model | African American adults in the South-eastern US | Entertainment | Educate nutrition and healthy eating | Users learn how to make healthier meal choices by ordering healthy menu in the game | |
35. | Not indicated | Not explicitly specified | Tracking | Self-monitoring system | Providing a self-monitoring and expert guidance system on physical activities and calorie intakes | |
36. | Self-awareness | Overweight and obese adults | Tracking | Weight management | Users track their caloric balance by recording food intake and physical activity on their mobile phones. Daily reminder messages are also sent via SMS messages to encourage compliance | |
37. | Run, tradie, run [81] | Persuasive design | Not explicitly specified | Entertainment | To increase physical activity | A player can purchase the in-game commodities using points that are earned by performing real physical activity |
38. | Not indicated | Not explicitly specified | Enforcing social influence | Dietetic monitoring and assessment | Users keep daily Personal Health Record (PHR) of their food intake and daily exercise, and to share them with a social network. | |
39. | Transtheoretical model and Social Cognitive Theory | Adult | Enforcing social influence | Increasing physical activity | Users physical activities are tracked through the fluctuation signal strength of their mobile phone and the results are shared with their peer | |
40. | Not indicated | Adolescent girls | Entertainment | To increase physical activity | Promoting physical fitness through addiction to an ongoing and compelling episodic interactive story whose progression is tied to exercise activities | |
41. | Not indicated | Not explicitly specified | Entertainment | Increasing physical activity | Users are encouraged to perform physical activity by solving quests and performing sports | |
42. | StepUp [90] | Not indicated | UAE population | Tracking | Increasing physical activity | It provides sensor-enabled mobile phones to automatically infer the number of steps the user walked and give the user a quantitative measure of his or her daily activities |
43. | Not indicated | Not explicitly specified | Tracking | Automatic recording of food intake | Users take mages of the meal which are then used to recognise, classify and estimate the volume and calorie content of the meal | |
44. | Persuasive design | Children | Entertainment | To motivate healthy eating practice | Users learn about healthy eating by sending photos of the food they consumed to their virtual pet | |
45. | Triple beat [96] | Persuasive design | Runners | Entertainment | To optimise physical activity | assists runners in achieving predefined exercise goals via musical feedback and two persuasive techniques: a glanceable interface for increased personal awareness and a virtual competition |
46. | Goal-setting, Transtheoretical Model of Behaviour Change | Not explicitly specified | Tracking | To increase physical activity | Users can journal and review their physical activities and are shown abstract glanceable display of their physical activities each week on their phone’s background screen | |
47. | Not indicated | Individuals engaged in a weight lost program (meal replacement) | Tracking | Monitoring food intake and weight data | A user is proactively prompted and reminded to interact with the application & initiate health and self-monitoring related tasks | |
48. | Walk2Build [104] | Social participation | Not explicitly specified | Entertainment | To increase physical activity | Recorded GPS data and distance travelled are converted into steps and submitted to a server to create a city which can then be shared with other users |
49. | CBT-based self-management | Not explicitly specified | Tracking | Monitoring lifestyle | Users can journal and review their lifestyle (weight, level of exercise, food intake, etc.) | |
50. | WiFi treasure hunt [109] | Not indicated | School children and college students | Entertainment | To increase physical activity | A user is assigned with a random running tour consisting 10 locations with tree of the selected locations will have “hidden treasures” |
51. | Wockets [110] | Not indicated | Not explicitly specified | Tracking | Monitoring physical activities | Capturing raw motion data to discriminate between activity types or to more accurately estimate energy expenditure |
52. | World of workout [111] | Not indicated | College students and gamers | Entertainment | To increase physical activity | A user levels up by working towards their goals and completing quests by achieving required number of steps |
Appendix 2: A detailed review of mobile phone applications from UCD perspective
Final outcome of studies | UCD key principles | |||||||
---|---|---|---|---|---|---|---|---|
Understanding of users, tasks and environment | User involvement throughout design and development | Design was driven and refined by user-centred evaluation | Iterative design process | Addressing the whole user experience | Inclusion of multidisciplinary skills and perspective | |||
1. | Fully functioning prototype | Not indicated | Not indicated | Not indicated | Not indicated | Not indicated | Yes | |
2. | Limited functioning prototype | User interviews with limited number of users (despite broad definition of users) for concept development | Users were involved in design concept refinement and evaluation of prototype. Methods adopted were low-fidelity prototyping, video prototyping, interviews and focus group | Yes | Yes | Yes | Yes | |
3. | Fully functioning prototype | Survey and focus group were performed for targeted end-users | Users were involved in concept development and evaluation of prototype | Not indicated | Not indicated | Yes | Yes | |
4. | Fully functioning prototype | Not indicated | Users were involved to validate automatic recognition of physical activities as well as design refinement for food diary (focus groups) | Yes | Yes | Not applicable | Yes | |
5. | Fully functioning prototype | Informal interviews with dietitian; followed by exploratory field interviews and ethnography with targeted end-user | Users were involved in design concept refinement and evaluation of prototype. Methods adopted were low- and high-fidelity prototyping, interviews and questionnaires | Yes | Yes | Yes | Yes | |
6. | Fully functioning prototype | Scenarios were used to explore context of use but no users were involved | Plan to involve user to evaluate high-fidelity prototype | Not indicated | Not indicated | Not applicable | Not indicated | |
7. | Fully functioning prototype | Not indicated | Users were only involved to validate automatic recognition of physical activities | Not indicated | Not indicated | Not indicated | Not indicated | |
8. | Fully functioning prototype | Not indicated | Not indicated | Not indicated | Not indicated | Not indicated | Not indicated | |
9. | DietCam [39] | Fully functioning prototype | Not indicated | Not indicated | Not indicated | Not indicated | Not indicated | Not indicated |
10. | DiTS [40] | Fully functioning prototype | Not indicated | Users were involved in the evaluation of high-fidelity prototype | Not indicated | Not indicated | Yes | Yes |
11. | ExerTrek [41] | Fully functioning prototype | Not indicated | Users were only involved in the evaluation of prototype | Not indicated | Not indicated | Not indicated | Yes |
12. | Fully functioning prototype | Extensive user studies were performed for concept development | Users were involved in design concept refinement and evaluation of prototype. Methods adopted were low- and high-fidelity prototyping, focus groups interviews and questionnaires | Yes | Yes | Yes | Yes | |
13. | Fitness tour [44] | Fully functioning prototype | Not indicated | Users are planned to be involved in the evaluation of the application | Not indicated | Not indicated | Not indicated | Not indicated |
14. | Fully functioning prototype | Not indicated | Not indicated | Not indicated | Not indicated | Not indicated | Not indicated | |
15. | Food fight [47] | Fully functioning prototype | Interviews were conducted with targeted end-users and stakeholders | Users were involved in design concept refinement and evaluation of prototype. Methods adopted were low- and high-fidelity prototyping and interviews | Yes | Yes | Yes | Yes |
16. | Fully functioning prototype | Not indicated | Users were involved in the evaluation of early prototype | Yes | Yes | Yes | Yes | |
17. | HealthAware [50] | Fully functioning prototype | Not indicated | Users were involved to validate automatic recognition of physical activities and a really limited user interface evaluation. | Not indicated | Not indicated | Not indicated | Not indicated |
18. | Fully functioning prototype | Not indicated | Users were involved to validate functions of the prototype | Not indicated | Not indicated | Yes | Yes | |
19. | HyperFit [53] | Fully functioning prototype | Consumer survey and interviews with stakeholders | Users and stakeholders were involved in design concept refinement and evaluation of prototype | Yes | Yes | Yes | Yes |
20. | Fully functioning prototype | End-users and expert interview were performed | Users were involved in concept development and evaluation of prototype | Yes | Yes | Yes | Yes | |
21. | Impact [56] | Fully functioning prototype | End-users studies were performed to establish system features | Users were involved in concept development and evaluation of prototype | Yes | Yes | Yes | Yes |
22. | Into [57] | Fully functioning prototype | End-users studies were performed to refine the concept and design aspects | Users were involved in concept development and evaluation of prototype | Yes | Yes | Yes | Yes |
23. | KnowME [58] | Fully functioning prototype | Not indicated | Users were only involved to validate energy expenditure capturing | Not indicated | Not indicated | Not indicated | Not indicated |
24. | LocoSnake [59] | Fully functioning prototype | Not indicated | Users were involved in the evaluation of prototype | Not indicated | Not indicated | Yes | Not indicated |
25. | Luften [60] | Limited functioning prototype | Not indicated | Not indicated | Not indicated | Not indicated | Not indicated | Not indicated |
26. | Fully functioning prototype | Not indicated | Users were involved in the evaluation of early prototype | Yes | Yes | Yes | Yes | |
27. | Mobile Snack [63] | Fully functioning prototype | Not indicated | Multiple cognitive walkthroughs were used for design concept refinement. Users were only involved in the evaluation of prototype through questionnaire | Yes | Yes | Yes | Yes |
28. | Monster and Gold [64] | Fully functioning prototype | Not indicated | Users were involved in the evaluation of high-fidelity prototype | Yes | Yes | Yes | Yes |
29. | Fully functioning prototype | Not indicated | Users were involved in the evaluation of high-fidelity prototype | Yes | Yes | Not indicated | Yes | |
30. | Fully functioning prototype | Not indicated | Users were only involved in the evaluation of high-fidelity prototype | Not indicated | Not indicated | Not indicated | Yes | |
31. | Move2PlayKids [69] | Limited functioning prototype | Not indicated | Users were involved in the evaluation of a limited functioning prototype | Not indicated | Not indicated | Not indicated | Yes |
32. | Fully functioning prototype | Not indicated | Users were only involved in the evaluation of high-fidelity prototype | Not indicated | Not indicated | Yes | Yes | |
33. | Fully functioning prototype | Not indicated | Users were only involved in the evaluation of high-fidelity prototype | Not indicated | Not indicated | Yes | Yes | |
34. | Fully functioning prototype | Not indicated | Users were only involved in the evaluation of high-fidelity prototype | Not indicated | Yes | Yes | Yes | |
35. | Fully functioning prototype | Not indicated | Users were only involved in the evaluation of high-fidelity prototype | Not indicated | Not indicated | Not indicated | Yes | |
36. | Fully functioning prototype | Scenarios were used to explore context of use but no users were involved | Users were only involved in the evaluation of high-fidelity prototype | Yes | Yes | Yes | Yes | |
37. | Run, tradie, run [81] | Fully functioning prototype | End-users studies were performed to refine the concept and design aspects | Users were involved in concept development and will be included in the evaluation of prototype | Yes | Yes | Yes | Yes |
38. | Fully functioning prototype | Not indicated | Users were only involved in the evaluation of high-fidelity prototype | Not indicated | Not indicated | Yes | Yes | |
39. | Fully functioning prototype | Not indicated | Users were only involved in the evaluation of high-fidelity prototype | Not indicated | Not indicated | Yes | Yes | |
40. | Fully functioning prototype | Not indicated | Not indicated | Not indicated | Not indicated | Not indicated | Not indicated | |
41. | Limited functioning prototype | Evaluation pilot on the concept of SpyFeet | Users were involved in the refinement of the SpyFeet concept | Yes | Yes | Yes | Yes | |
42. | StepUp [90] | Fully functioning prototype | Not indicated | Users were only involved to validate accuracy of the system | Not indicated | Not indicated | Not indicated | Not indicated |
43. | Fully functioning prototype | Not indicated | Users were only involved in the evaluation of high-fidelity prototype | Not indicated | Yes | Yes | Yes | |
44. | Fully functioning prototype | Relevant stakeholders were consulted but no direct users involvement | Users were involved in the evaluation of prototype | Yes | Yes | Yes | Yes | |
45. | Triple beat [96] | Fully functioning prototype | Not indicated | Users were involved in the evaluation of prototype | Not indicated | Not indicated | Yes | Yes |
46. | Fully functioning prototype | Survey to potential users were performed | Users were involved in concept development and evaluation of prototype | Yes | Yes | Yes | Yes | |
47. | Walk2Build [102] | Limited functioning prototype | Not indicated | Users will be involved in the evaluation of a fully functioning prototype | Not indicated | Not indicated | Not indicated | Yes |
48. | Fully functioning prototype | Not indicated | Users were involved in the evaluation of prototype | Not indicated | Not indicated | Not indicated | Not indicated | |
49. | Fully functioning prototype | Not indicated | Users were involved in concept development and evaluation of prototype | Yes | Yes | Yes | Yes | |
50. | WiFi treasure hunt [109] | Fully functioning prototype | Not indicated | Users are planned to be involved in the evaluation of the application | Not indicated | Not indicated | Not indicated | Not indicated |
51. | Wockets [110] | Fully functioning prototype | Participatory design with potential users were performed | Users were involved in concept development | Yes | Yes | Not applicable | Yes |
52. | World of workout [111] | Limited functioning prototype | Not indicated | Users were involved in the refinement of the World of Workout concept | Yes | Yes | Yes | Yes |
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Hermawati, S., Lawson, G. Managing obesity through mobile phone applications: a state-of-the-art review from a user-centred design perspective. Pers Ubiquit Comput 18, 2003–2023 (2014). https://doi.org/10.1007/s00779-014-0757-4
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DOI: https://doi.org/10.1007/s00779-014-0757-4